---
title: Kinetica
---

[Kinetica](https://www.kinetica.com/) is a real-time database purpose built for enabling
analytics and generative AI on time-series & spatial data.

## Chat Model

The Kinetica LLM wrapper uses the [Kinetica SqlAssist
LLM](https://docs.kinetica.com/7.2/sql-gpt/concepts/) to transform natural language into
SQL to simplify the process of data retrieval.

See [Kinetica Language To SQL Chat Model](/oss/integrations/chat/kinetica) for usage.

```python
from langchain_community.chat_models.kinetica import ChatKinetica
```

## Vector Store

The Kinetca vectorstore wrapper leverages Kinetica's native support for [vector
similarity search](https://docs.kinetica.com/7.2/vector_search/).

See [Kinetica Vectorstore API](/oss/integrations/vectorstores/kinetica) for usage.

```python
from langchain_community.vectorstores import Kinetica
```

## Document Loader

The Kinetica Document loader can be used to load LangChain [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) from the
[Kinetica](https://www.kinetica.com/) database.

See [Kinetica Document Loader](/oss/integrations/document_loaders/kinetica) for usage

```python
from langchain_community.document_loaders.kinetica_loader import KineticaLoader
```

## Retriever

The Kinetica Retriever can return documents given an unstructured query.

See [Kinetica VectorStore based Retriever](/oss/integrations/retrievers/kinetica) for usage
